Impulsivity Moderates the Effect of Neurofeedback Training on the Contingent Negative Variation in Autism Spectrum Disorder

Abstract

Background: The contingent negative variation (CNV) is a well-studied indicator of attention- and expectancy-related processes in the human brain. An abnormal CNV amplitude has been found in diverse neurodevelopmental psychiatric disorders. However, its role as a potential biomarker of successful clinical interventions in autism spectrum disorder (ASD) remains unclear.

Methods: In this randomized controlled trial, we investigated how the CNV changes following an intensive neurofeedback training. Therefore, twenty-one adolescents with ASD underwent 24 sessions of slow cortical potential (SCP) neurofeedback training. Twenty additional adolescents with ASD formed a control group and received treatment as usual. CNV waveforms were obtained from a continuous performance test (CPT), which all adolescents performed before and after the corresponding 3-month long training period. In order to utilize all available neural time series, trial-based area under the curve values for all four electroencephalogram (EEG) channels were analyzed with a hierarchical Bayesian model. In addition, the model included impulsivity, inattention, and hyperactivity as potential moderators of change in CNV.

Results: Our model implies that impulsivity moderates the effects of neurofeedback training on CNV depending on group. In the control group, the average CNV amplitude decreased or did not change after treatment as usual. In the experimental group, the CNV changed depending on the severity of comorbid impulsivity symptoms. The average CNV amplitude of participants with low impulsivity scores decreased markedly, whereas the average CNV amplitude of participants with high impulsivity increased.

Conclusion: The degree of impulsivity seems to play a crucial role in the changeability of the CNV following an intensive neurofeedback training. Therefore, comorbid symptomatology should be recorded and analyzed in future EEG-based brain training interventions.

Clinical trial registration: https://www.drks.de, identifier DRKS00012339.

Keywords: autism spectrum disorder; contingent negative variation; executive functions; hierarchical models; impulsivity; neurofeedback; slow cortical potentials.

FIGURE 1

Experimental timeline for the neurofeedback group. Participants received 24 sessions of neurofeedback, including a 1 week break between sessions 12 and 13. Every session entailed three blocks and each block consisted of either 40 Feedback or 40 Transfer trials. The trials included a baseline, a training, and a reinforcement phase. In the reinforcement phase, participants received positive visual feedback (reward) if the trial was successful and no feedback if the trial was not successful. Copyright Neurofeedback Screens © neuroConn GmbH/neurocare group AG.

FIGURE 2

Grand-averaged CNV waveforms for each of the four channels (FCz, Fz, Cz, and Pz) obtained from each group (neurofeedback vs. control) and time point (pre vs. post). The light blue regions indicate the time-window considered for computing the mean CNV amplitude within each trial of the CPT.

FIGURE 3

Binary moderator model results. Model-based predictions of population-level CNV amplitudes across both levels of the binary moderator. Colored points indicate predicted means. Red, Neurofeedback Group (NFB); Blue, Control Group. Black points indicate empirical means. Notice the difference between predicted and observed means due to shrinkage. Error bars indicate 95% credibility intervals (predictive uncertainty).

FIGURE 4

Fine-grained moderator model results. Model-based predictions of population-level means across low and high scores of the moderator variables: A, Attention; H, Hyperactivity; I, Impulsivity. Points indicate predicted means: Red, Neurofeedback Group (NFB); Blue, Control Group. Error bars indicate 95% credibility intervals (predictive uncertainty). Only model-based predictions are depicted, since quasi-continuous moderators are conditioned on concrete values and no discrete subgroups were built for analysis.